MacBook Pro M4 Pro 24GB经济之选
24 GB Unified (+8)
B
This setup is broadly balanced for this model.53.3 tok/s 解码
~$1,999 MSRP
Can Granite 3.1 8B run on RTX 4060 Ti 16GB?
YES — Runs Great
B57Good
Estimated from fit model
Granite 3.1 8B needs ~9.3 GB VRAM. RTX 4060 Ti 16GB has 16.0 GB. With Q4_K_M quantization, expect ~50 tok/s.
Runtime: llama.cppCapacity: RoomyBandwidth: LowStack: StandardBottleneck: Balanced
Operating mode
Choose the run profile you care about
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Q4_K_M (Medium quality) — 9.3 GB, 53.3 tok/s, Runs well
9.3 GB required16.0 GB available
58% VRAM used
Fit status
Runs well
Decode
53.3 tok/s
TTFT
3635 ms
Safe context
71K
Memory
9.3 GB / 16.0 GB
Memory breakdown
Weights4.9 GB
KV Cache2.0 GB
Runtime0.9 GB
Headroom1.6 GB
See how fast it feels
See how fast it feelsGranite 3.1 8B on RTX 4060 Ti 16GB
1st promptCold start — includes initialization
>Write a Python function to sort a list
Here's a Python function that sorts a list using quicksort:
def quicksort(arr):
if len(arr) <= 1:
return arr
pivot = arr[len(arr) // 2]
left = [x for x in arr if x < pivot]
middle = [x for x in arr if x == pivot]
right = [x for x in arr if x > pivot]
return quicksort(left) + middle + quicksort(right)
# Example usage
numbers = [3, 6, 8, 10, 1, 2, 1]
print(quicksort(numbers)) # [1, 1, 2, 3, 6, 8, 10]
The algorithm picks a pivot, partitions the list into smaller, equal, and larger elements, then recursively sorts each partition and concatenates the results.
2nd promptWarm — model ready, no init overhead
>Now add type hints and a docstring
def quicksort(arr: list[int]) -> list[int]:
"""Sort a list using the quicksort algorithm.
Args:
arr: List of integers to sort.
Returns:
A new sorted list.
"""
if len(arr) <= 1:
return arr
pivot = arr[len(arr) // 2]
left = [x for x in arr if x < pivot]
middle = [x for x in arr if x == pivot]
right = [x for x in arr if x > pivot]
return quicksort(left) + middle + quicksort(right)
Added type hints for the input and return type, plus a Google-style docstring.
Estimated: 53.3 tok/s decode · 3.6s TTFT (warm) · 133 tok/s prefill
What limits this setup
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 49.5 tok/s | 2131 ms | 71K |
| Coding | B | Runs well | 49.5 tok/s | 3908 ms | 71K |
| Agentic Coding | B | Runs well | 49.5 tok/s | 5684 ms | 71K |
| Reasoning | B | Runs well | 49.5 tok/s | 4618 ms | 71K |
| RAG | B | Runs well | 49.5 tok/s | 7105 ms | 71K |
Quantization options
How Granite 3.1 8B (8B params) fits at each quantization level on RTX 4060 Ti 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C52 |
Q3_K_S | 3 | 3.9 GB | Low | C52 |
NVFP4 | 4 | 4.5 GB | Medium | C53 |
Q4_K_M | 4 | 4.9 GB | Medium | C53 |
Q5_K_M | 5 | 5.8 GB | High | C54 |
Q6_K | 6 | 6.6 GB | High | C55 |
Q8_0Best for your GPU | 8 | 8.6 GB | Very High | B56 |
F16 | 16 | 16.4 GB | Maximum | F0 |
Get started
Copy-paste commands to run Granite 3.1 8B on your machine.
Run
ollama run granite3.1-dense升级选项
能流畅运行 Granite 3.1 8B 的硬件
Frequently asked questions
Can RTX 4060 Ti 16GB run Granite 3.1 8B?
Yes, RTX 4060 Ti 16GB can run Granite 3.1 8B with a B grade (Runs well). Expected decode speed: 49.5 tok/s.
How much VRAM does Granite 3.1 8B need?
Granite 3.1 8B (8B parameters) requires approximately 9.3 GB of memory with Q4_K_M quantization.
What is the best quantization for Granite 3.1 8B?
The recommended quantization for Granite 3.1 8B is Q4_K_M, which balances quality and memory efficiency.
What speed will Granite 3.1 8B run at on RTX 4060 Ti 16GB?
On RTX 4060 Ti 16GB, Granite 3.1 8B achieves approximately 49.5 tokens per second decode speed with a time-to-first-token of 3908ms using Q4_K_M quantization.
Can RTX 4060 Ti 16GB run Granite 3.1 8B for coding?
For coding workloads, Granite 3.1 8B on RTX 4060 Ti 16GB receives a B grade with 49.5 tok/s and 71K context.
What context window can Granite 3.1 8B use on RTX 4060 Ti 16GB?
On RTX 4060 Ti 16GB, Granite 3.1 8B can safely use up to 71K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.
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<iframe src="https://willitrunai.com/embed/granite-3.1-8b-on-rtx-4060-ti-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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